Basic Research for Recognizing Road Objects Using Point Cloud Data by Machine Learning

Abstract

In Japan, where the aging of social infrastructure is advancing, the momentum for working on infrastructure maintenance throughout society is increasing. Focusing on the road field, laser scanners that can measure the three-dimensional shape of the surrounding environment as point cloud data are attracting attention. Since laser scanners can grasp a wide range of three-dimensional shapes in a short time, research in improving the efficiency of road maintenance using measured point cloud data is being promoted. However, point cloud data is a collection of XYZ coordinates, and these points do not contain information on road objects. It is necessary to select point cloud data relating to the necessary road objects in accordance with the intended application in order to achieve efficient operation in practice. Therefore, technology to automatically recognize road objects from out of a large amount of point cloud data is required. In this research, we propose a method for recognizing road objects using point cloud data by machine learning.